DevOps Archives

Tech Optimizer

November 24, 2025

When prevention fails: the case for building cyber resilience, not walls

Organizations are shifting from a "fortress" mentality in cybersecurity to a focus on resilience, recognizing that the attack surface has expanded due to hybrid cloud environments, remote work, and AI. True cyber-resilience involves integrating security into all operations, utilizing automation and AI for threat detection and response, and implementing real-time data replication and immutable backups for quick service restoration. Continuous cyber-simulations are essential for preparedness, and a culture of security requires involvement from all employees. Resilience is increasingly viewed as a competitive advantage, influencing customer trust and enabling faster innovation, including the exploration of quantum-safe cryptography for future threats.

Tech Optimizer

November 21, 2025

Critical pgAdmin4 Vulnerability Lets Attackers Execute Remote Code on Servers

A severe remote code execution (RCE) vulnerability, designated as CVE-2025-12762, has been identified in pgAdmin4, affecting versions up to 9.9. This flaw allows attackers to execute arbitrary commands on the hosting server due to improper handling of code injection during server-mode restores from PLAIN-format dump files. It can be exploited by authenticated users with low privileges and requires only network access, classified as critical with a CVSS v3.1 score of 9.3 out of 10. The vulnerability is linked to unsafe command construction during the restore process, and pgAdmin developers have addressed it in version 10.0. Organizations are advised to upgrade to pgAdmin 10.0 or later, disable PLAIN-format restores, and audit access controls.

Tech Optimizer

November 5, 2025

pgEdge Adds Ability to Distribute Postgres Across Multiple Kubernetes Clusters

pgEdge has enhanced its open-source Postgres database distribution to enable deployment across multiple Kubernetes clusters, allowing IT teams to deploy logical instances of Postgres databases in a distributed computing environment. This capability facilitates horizontal scaling, reduces latency, and improves performance. IT teams can choose between two deployment options: a minimal version with essential pgEdge extensions and a standard edition with additional extensions like pgVector, PostGIS, and pgAudit. The core database is distributed under an OSI-approved PostgreSQL License, with pgEdge Containers on Kubernetes available via the GitHub Container Registry. The new deployment method involves distributed containers and is supported by the Cloud Native Computing Foundation (CNCF). pgEdge has also updated its Helm chart to support pgEdge Containers on Kubernetes and Patroni for high-availability Postgres instances. The distribution extent depends on the application's nature and network bandwidth, with at least one organization successfully distributing a Postgres instance across 20 clusters. There is a growing trend in cloud-native database deployments, particularly for Postgres, indicating an increasing demand for collaboration between database administrators and DevOps teams managing Kubernetes clusters.

Tech Optimizer

November 5, 2025

Inside EDB Postgres AI: The end-to-end platform for data, devops, and genAI readiness

The organization is a leading contributor to the open-source PostgreSQL community and has expanded its focus to include Generative AI (GenAI) technologies. They are addressing challenges related to data sovereignty and transforming enterprise data into AI-ready formats. The integration of AI into enterprise operations is becoming crucial, and the user base has evolved from primarily database administrators (DBAs) to include application teams and strategic infrastructure roles like platform engineering. This shift reflects a trend toward collaboration across various roles in data management and AI integration.

AppWizard

October 28, 2025

Arattai Rising: Can India’s Homegrown Messenger Challenge WhatsApp’s Throne?

Arattai, a messaging app in India, gained significant traction in September and October 2025, reaching over 5 million downloads on certain days and surpassing established platforms like Telegram and Snapchat. Its rise was supported by media attention, endorsements from government officials, and alignment with Prime Minister Modi's Swadeshi initiative. Union Home Minister Amit Shah's switch to Zoho email led to a 100-fold increase in Arattai's traffic within three days. The app offers end-to-end encryption for voice and video calls but lacks full encryption for text messages by default. It has a “secret chat” feature and plans to implement comprehensive encryption. User data is stored in Indian data centers, and the app aims to maintain a privacy-focused approach without relying on public cloud providers. Arattai faces challenges in competing with WhatsApp, which has over 500 million users and offers extensive features such as UPI payments and default encryption. For long-term success, Arattai needs to standardize encryption, enhance its infrastructure, and build an ecosystem with integrated payment solutions and business tools. Overcoming user inertia from WhatsApp, establishing a strong brand identity, and navigating regulatory scrutiny are also critical for its growth.

Tech Optimizer

October 28, 2025

Optimize and troubleshoot database performance in Amazon Aurora PostgreSQL by analyzing execution plans using CloudWatch Database Insights

Amazon Web Services (AWS) offers monitoring tools for Amazon Relational Database Service (RDS) and Amazon Aurora databases, including Amazon CloudWatch Database Insights, which helps analyze SQL execution plans for troubleshooting and optimizing SQL query performance in Aurora PostgreSQL clusters. The PostgreSQL query optimizer generates multiple execution strategies for SQL queries and selects the most efficient based on cost estimation. A query access plan details the execution strategy, which can be analyzed using the EXPLAIN command. In December 2024, AWS launched CloudWatch Database Insights, supporting Aurora and RDS engines, aimed at helping DevOps engineers, developers, and DBAs identify and resolve database performance issues. The tool has Advanced and Standard modes, with SQL execution plan analysis available in Advanced mode. To analyze SQL execution plans, users can access CloudWatch Database Insights, review performance metrics, and compare execution plans side-by-side. For example, one execution plan may use a sequential scan while another uses an index scan, revealing differences in query performance. When troubleshooting performance degradation, DBAs can compare execution plans over time to identify changes affecting performance. For instance, dropping indexes can lead to suboptimal execution plans and increased query costs. Analyzing execution plans can uncover inefficiencies, such as missing indexes or outdated statistics. For example, a query summarizing customer spending revealed that the work_mem parameter was set too low, causing disk-based sorting instead of in-memory sorting, which degraded performance. Increasing the work_mem parameter improved query execution efficiency. CloudWatch Database Insights simplifies the process of identifying performance bottlenecks and optimizing query performance through visualizations and execution plan comparisons.

Tech Optimizer

October 5, 2025

EDB Advances PostgreSQL 18 With AI-Ready Features and Enterprise Enhancements

EnterpriseDB (EDB) has contributed to PostgreSQL 18, which includes over 200 new features aimed at enhancing support for AI, hybrid deployments, and enterprise performance. Key enhancements include OAuth authentication, optimizer enhancements, Kubernetes-friendly extension management, SQL standards compliance, and flexible index support. EDB's research shows that 35% of enterprises are considering PostgreSQL for AI workloads, with organizations focused on data sovereignty reporting a 12.5 times greater return on investment. EDB has also published "Building a Data and AI Platform with PostgreSQL" to help enterprises build scalable AI systems and is preparing for PostgreSQL 19 and the EDB Postgres AI Database, which will feature advanced functionalities.

Tech Optimizer

September 7, 2025

Automating vector embedding generation in Amazon Aurora PostgreSQL with Amazon Bedrock

Vector embeddings are mathematical representations that enhance the processing of unstructured data in applications like semantic search and recommendation systems. Maintaining current vector embeddings is essential for AI functionalities, especially when using Retrieval-Augmented Generation (RAG) solutions. Amazon Bedrock offers managed solutions for embedding generation, but organizations may opt for custom vector databases using PostgreSQL with the pgvector extension for specific needs. A vector database setup involves creating a system to generate and update embeddings in response to data changes. The workflow includes identifying data changes, sending content to embedding models, receiving embeddings, and storing them alongside original data. Amazon Titan is highlighted for its performance in generating embeddings. Five implementation approaches for automating the embedding workflow are discussed: 1. **Database triggers with the aws_ml extension (synchronous)**: This method uses PostgreSQL triggers to generate embeddings immediately upon data changes, ensuring real-time consistency but potentially increasing transaction duration. 2. **Database triggers with the aws_lambda extension (synchronous)**: This approach decouples embedding generation from database operations by invoking a Lambda function synchronously, allowing for more complex processing but still blocking transactions. 3. **Database triggers with the aws_lambda extension (asynchronous)**: Here, triggers invoke Lambda functions asynchronously, allowing database operations to proceed without waiting for embedding generation, which enhances performance but introduces eventual consistency. 4. **Amazon SQS queue with Lambda batch processing (asynchronous)**: This method sends messages to an SQS queue for batch processing by a Lambda function, optimizing for scalability and resilience but increasing latency between data insertion and embedding availability. 5. **Periodic updates scheduled with the pg_cron extension (asynchronous)**: This approach schedules jobs to process embeddings in batches, improving throughput and cost-efficiency while increasing the delay between data changes and embedding updates. Each approach has its pros and cons, including considerations for transaction blocking, error handling, latency, and scalability. The choice of method depends on specific use case requirements, such as the need for real-time updates versus batch processing efficiency.

AppWizard

August 24, 2025

Week in review: Covertly connected and insecure Android VPN apps, Apple fixes exploited zero-day

A study by Arizona State University and Citizen Lab found that three families of Android VPN apps, with over 700 million downloads, have significant security vulnerabilities. Apple has released a fix for a zero-day vulnerability (CVE-2025-43300) that was being exploited in targeted attacks. Researchers from the University of Melbourne and Imperial College London developed a method using lightweight large language models to improve incident response planning. The FBI and Cisco warned about a Russian threat group exploiting an old Cisco vulnerability (CVE-2018-0171) to compromise critical infrastructure. Fog Security researchers discovered a flaw in AWS’s Trusted Advisor tool that could mislead users about the security of their data. AI is now being used in security operations centers to reduce alert noise and assist analysts. U.S. federal prosecutors charged an individual linked to the Rapper Bot DDoS botnet. Nikoloz Kokhreidze discussed the strategic choice between hiring a fractional or full-time Chief Information Security Officer for B2B companies. Commvault patched four vulnerabilities that risked remote code execution. Jacob Ideskog highlighted security risks posed by AI agents. VX Underground released an exploit for two SAP Netweaver vulnerabilities (CVE-2025-31324, CVE-2025-42999). Healthcare organizations are preparing for new password security risks in 2025 that may threaten HIPAA compliance. Researchers identified a spear-phishing campaign using the Noodlophile infostealer. Financial institutions are increasingly using open-source intelligence tools to combat money laundering. Greg Bak discussed security risks for DevOps teams in the cloud. NIST released guidelines for detecting morph attacks. Organizations face six challenges in implementing machine learning and AI security. Recep Ozdag discussed vulnerabilities in airport and airline systems. Google introduced new AI and cloud security capabilities at the Cloud Security Summit 2025. Cybersecurity myths continue to complicate the security landscape. LudusHound is an open-source tool that replicates an Active Directory environment for testing. Buttercup is an AI-powered platform for automated vulnerability management in open-source software. The book "Data Engineering for Cybersecurity" addresses challenges in managing logs and telemetry data. A selection of current cybersecurity job openings has been compiled. A forthcoming webinar will discuss AI and SaaS security risks. The iStorage datAshur PRO+C is a USB-C flash drive with AES-XTS 256-bit hardware encryption. New infosec products were released by companies such as Doppel, Druva, LastPass, and StackHawk.

Tech Optimizer

August 18, 2025

Critical PostgreSQL Flaws Allow Code Injection During Restoration

The PostgreSQL Global Development Group released emergency security updates on August 14, 2025, to address three critical vulnerabilities affecting PostgreSQL versions 13 through 17. The vulnerabilities include: 1. CVE-2025-8714: Allows arbitrary OS code execution via pg_dump meta-commands, with a CVSS score of 8.8. 2. CVE-2025-8715: Facilitates code/SQL injection through improper newline handling in object names, also with a CVSS score of 8.8. 3. CVE-2025-8713: Exposes sensitive data via optimizer statistics, with a CVSS score of 3.1. Organizations are advised to upgrade to PostgreSQL versions 17.6, 16.10, 15.14, 14.19, or 13.22 immediately. Cloud providers have begun emergency fleet updates, and development teams should audit their CI/CD pipelines for pg_dump usage. The vulnerabilities were disclosed responsibly by several individuals, and PostgreSQL 13 will reach its end-of-life on November 13, 2025.